WO2019196109A1 - 一种抑制图像伪彩的方法及装置 - Google Patents
一种抑制图像伪彩的方法及装置 Download PDFInfo
- Publication number
- WO2019196109A1 WO2019196109A1 PCT/CN2018/083035 CN2018083035W WO2019196109A1 WO 2019196109 A1 WO2019196109 A1 WO 2019196109A1 CN 2018083035 W CN2018083035 W CN 2018083035W WO 2019196109 A1 WO2019196109 A1 WO 2019196109A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- component
- image
- interpolation
- pseudo color
- pixel point
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 47
- 230000001629 suppression Effects 0.000 claims abstract description 30
- 238000004590 computer program Methods 0.000 claims description 22
- 238000004364 calculation method Methods 0.000 claims description 11
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 230000002547 anomalous effect Effects 0.000 claims description 5
- 238000012545 processing Methods 0.000 abstract description 11
- 230000006870 function Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 239000003086 colorant Substances 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000002708 enhancing effect Effects 0.000 description 3
- 238000009499 grossing Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000000295 complement effect Effects 0.000 description 2
- 229910044991 metal oxide Inorganic materials 0.000 description 2
- 150000004706 metal oxides Chemical class 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- 206010034972 Photosensitivity reaction Diseases 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000003706 image smoothing Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000036211 photosensitivity Effects 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
Definitions
- the invention belongs to the technical field of image processing, and in particular relates to a method and a device for suppressing image false color.
- each photosensitive spot can only be one of red (R, R) green (Green, G) blue (Blue, B).
- RGB red
- Green, G green
- Blue, B blue
- the pixel value of each pixel in the image is regarded as the entry address of the entry of the color lookup table, and the corresponding RGB intensity value is searched for interpolation, and the interpolated pixel color is displayed to display the real image.
- image interpolation it is easy to generate false color due to inaccurate estimation of the interpolation direction of image pixels.
- the embodiments of the present invention provide a method and an apparatus for suppressing image pseudo-color to solve the color error caused by the inaccurate interpolation direction determination result in the prior art, and cannot effectively suppress the regional pseudo-color phenomenon of the image. , causing distortion in the image display.
- a first aspect of the embodiments of the present invention provides a method for suppressing image pseudo color, including:
- a pseudo color suppression image is obtained based on the target component.
- a second aspect of the embodiments of the present invention provides an apparatus for suppressing image pseudo color, including:
- An image obtaining unit configured to acquire an original image and an interpolated image obtained by performing color filter array interpolation on the original image
- a type determining unit configured to determine a pseudo color type to which the pseudo color image in the interpolation image belongs
- a component determining unit configured to determine, at the pixel point in the pseudo color image, according to the pseudo color type, an original component of the original image, an interpolation component of the interpolation image, and a preset image pseudo color suppression policy Target component
- an image determining unit configured to obtain a pseudo color suppression image according to the target component.
- a third aspect of the embodiments of the present invention provides an apparatus for suppressing image pseudo color, comprising: a processor, an input device, an output device, and a memory, wherein the processor, the input device, the output device, and the memory are connected to each other, wherein
- the memory is for storing a computer program supporting the apparatus for performing the above method, the computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method of the first aspect above.
- a fourth aspect of an embodiment of the present invention provides a computer readable storage medium storing a computer program, the computer program including program instructions, the program instructions causing the processing when executed by a processor The method of the first aspect described above is performed.
- the embodiment of the present invention has the beneficial effects that: by acquiring an original image, performing color filter array interpolation on the original image to obtain an interpolated image; and determining a pseudo color to which the pseudo color image in the interpolated image belongs Determining a target component at a pixel point in the pseudo color image according to the pseudo color type, an original component of the original image, an interpolation component of the interpolation image, and a preset image pseudo color suppression strategy, and finally A pseudo color suppression image is obtained based on the target component.
- the difference between the original component value in the neighborhood of the central pixel point and the interpolated component value is calculated by the original image data before the interpolation and the interpolated image data, and the mode of the pseudo color is determined, and the component values in the original image are re-evaluated accordingly.
- FIG. 1 is a flowchart of a method for suppressing image pseudo color according to an embodiment of the present invention
- FIG. 2 is a flowchart of a method for suppressing image pseudo color according to another embodiment of the present invention.
- FIG. 3 is a schematic diagram of an apparatus for suppressing image pseudo color according to an embodiment of the present invention.
- FIG. 4 is a schematic diagram of an apparatus for suppressing image pseudo color according to another embodiment of the present invention.
- FIG. 5 is a schematic diagram of an apparatus for suppressing image pseudo color according to still another embodiment of the present invention.
- FIG. 1 is a flowchart of a method for suppressing image pseudo color according to an embodiment of the present invention.
- the execution subject of the method for suppressing image pseudo color in the embodiment is a device having an image processing function, including but not limited to a device such as a computer, a server, a tablet computer or a terminal.
- the method for suppressing image pseudo color shown in FIG. 1 may include the following steps:
- S101 Acquire an original image and an interpolated image obtained by performing color filter array interpolation on the original image.
- the existing image generating device converts an optical image into electronic data by using an electronic sensor, wherein the sensor of the digital camera is a light-sensitive charge coupled device (CCD) or a complementary metal oxide semiconductor (Complementary Metal Oxide Semiconductor).
- CCD charge-sensitive charge coupled device
- CMOS complementary metal oxide semiconductor
- RGB Red
- Green Green
- Blue Blue
- Sensors are more expensive.
- each of the photosensitive pixels There is a metal isolation layer between each of the photosensitive pixels, and the light passes through the microscope head and is filtered by the color filter to be projected onto the corresponding photosensitive element of the silicon. Therefore, only one color component can be acquired for each pixel of the sensor array. In order to obtain a full-color image, each pixel must estimate the other two colors lost by the pixel through its adjacent known color components. Component.
- each pixel in the original image includes only a portion of the spectrum, and the RGB values of each pixel must be determined by interpolation.
- Traditional interpolation methods are: nearest neighbor interpolation, bilinear interpolation, double square interpolation, double cubic interpolation, and other high order methods.
- Nearest neighbor interpolation and bilinear interpolation algorithms are prone to aliasing and the resulting pictures are of poor quality. Therefore, it is generally only used when the image quality is not high.
- Double-square interpolation and double-cube interpolation lose many high-frequency information while enhancing image smoothing. In many applications, the details are just as important, considering how to preserve the detail as much as possible while ensuring smoothing.
- the color filter array interpolation calculates the color component of each pixel by calculating the correlation coefficient between the three channels of the image.
- Color filter array interpolation methods are divided into heuristic and non-heuristic interpolation methods. Heuristics include edge direction interpolation, constant tone interpolation, high quality linear interpolation, weighted average interpolation, template matching interpolation and frequency domain filtering interpolation; non-heuristic including vector interpolation, Bayesian interpolation, pre-estimation least square error interpolation method .
- the edge direction interpolation method determines the blur at the edge of the image to be caused by cross-boundary interpolation. If the interpolation direction can be correctly determined, interpolation is performed only at the boundary direction along the boundary direction without crossing the boundary, thereby improving the inverse Mosaic image quality.
- the unknown information is calculated by calculating the horizontal vertical gradient and selecting the adjacent information in the direction with small gradient; the vector interpolation method treats the pixel as a vector in the RGB three-dimensional space, and minimizes the difference vector by making a difference to the adjacent pixel vector.
- An interpolation image obtained by performing color filter array interpolation on the original image.
- S102 Determine a pseudo color type to which the pseudo color image in the interpolation image belongs.
- the pseudo-color type is taken as an important factor for suppressing the image pseudo-color.
- the pseudo-color type can be used to The pseudo color type estimates the component values of the pixel points in the original image.
- S103 Determine a target component at a pixel point in the pseudo color image according to the pseudo color type, an original component of the original image, an interpolation component of the interpolation image, and a preset image pseudo color suppression strategy.
- determining the pixel point in the pseudo color image according to the pseudo color type After determining the pseudo color type, determining the pixel point in the pseudo color image according to the pseudo color type, the original component of the original image, the interpolation component of the interpolation image, and a preset image pseudo color suppression strategy Target component.
- the difference between the original component value in the neighborhood of the pixel point and the interpolated component value is calculated, and the pseudo color type of each pixel in the interpolation image is determined according to the difference, and the corresponding component at each pixel point of the original image is re-evaluated accordingly Value.
- Establishing and enhancing the G component at the R component or the B component after the interpolation of the pixel of the pixel, the B component at the R component, and the R component at the B component, and determining the G component at the G component by these component values The spatial difference between the component difference of the R component, the component difference between the G component and the B component, and finally the target component value at each component is re-evaluated based on the spatial correlation.
- the original component values before interpolation are referenced, and the spatial correlation after interpolation is re-enhanced, which can better suppress regional pseudo-color and directional false pseudo-color.
- the component values of the respective pixel points in the original image can be determined, that is, the pseudo color suppression image is obtained.
- an interpolated image obtained by acquiring an original image and performing color filter array interpolation on the original image; determining a pseudo color type to which the pseudo color image in the interpolated image belongs; according to the pseudo color type, the original An original component of the image, an interpolation component of the interpolated image, and a preset image pseudo color suppression strategy determine a target component at a pixel point in the pseudo color image; and obtain a pseudo color suppression image according to the target component.
- FIG. 2 is a flowchart of a method for suppressing image pseudo color according to an embodiment of the present invention.
- the execution subject of the method for suppressing image pseudo color in the embodiment is a device having an image processing function, including but not limited to a device such as a computer, a server, a tablet computer or a terminal.
- the method for suppressing image pseudo color shown in FIG. 2 may include the following steps:
- S201 Acquire an original image and an interpolated image obtained by performing color filter array interpolation on the original image.
- S202 Determine a pseudo color type to which the pseudo color image in the interpolation image belongs.
- the pseudo-color type is taken as an important factor for suppressing the image pseudo-color.
- the pseudo-color type can be used to The pseudo color type estimates the component values of the pixel points in the original image.
- step S202 may specifically include S2021 to S2022, as follows:
- S2021 Calculate a difference between the original component in the original image and an interpolation component corresponding to the original component in the interpolation image.
- the difference is calculated according to formula (1):
- Representing a component value in the original image Representing an interpolated component value corresponding to the original component in the interpolated image, i ⁇ ⁇ , ⁇ representing a spatial neighborhood set of the interpolated component.
- the spatial neighborhood of the interpolated component represents the interpolated components of the upper, lower, left, and right four pixel points adjacent to a certain pixel in the image, but the image processing in this embodiment can still be A larger neighborhood is performed, in which case the pixel has more than 4 neighborhood pixels.
- each pixel in the interpolated image obtained by interpolating the original image contains the R component, the G component, and the B component, and thus, for the original image.
- the difference calculation here is for the same component of the interpolated image as the component of the pixel in the original image.
- the component of a certain pixel in the original image is a G component
- the component at the pixel includes the R component, the G component, and the B component, and therefore,
- the difference here is the difference between the G component of the pixel in the original image and the G component of the pixel in the interpolated image.
- S2022 Determine, according to the difference, a pseudo color type to which the pseudo color image in the interpolation image belongs.
- S1022 specifically includes:
- the pseudo color type of the interpolated image is a weak pseudo color
- the pseudo color type of the interpolated image is the same direction pseudo color
- the pseudo color type of the interpolated image is an anomalous pseudo color
- ⁇ c is the preset pseudo color type threshold of component c.
- the pseudo-color type can be used to The pixel points in the image are estimated by component values.
- S203 Re-estimate the component estimation value at the pixel point according to the pseudo color type, the original component of the original image, and the interpolation component of the interpolation image.
- determining the pixel point in the pseudo color image according to the pseudo color type After determining the pseudo color type, determining the pixel point in the pseudo color image according to the pseudo color type, the original component of the original image, the interpolation component of the interpolation image, and a preset image pseudo color suppression strategy Target component.
- the difference between the original component value in the neighborhood of the pixel point and the interpolated component value is calculated, and the pseudo color type of each pixel in the interpolation image is determined according to the difference, and the corresponding component at each pixel point of the original image is re-evaluated accordingly Value.
- Establishing and enhancing the G component at the R component or the B component after the interpolation of the pixel of the pixel, the B component at the R component, and the R component at the B component, and determining the G component at the G component by these component values The spatial difference between the component difference of the R component, the component difference between the G component and the B component, and finally the target component value at each component is re-evaluated based on the spatial correlation.
- the original component values before interpolation are referenced, and the spatial correlation after interpolation is re-enhanced, which can better suppress regional pseudo-color and directional false pseudo-color.
- step S203 may specifically include:
- the pseudo color type is the weak pseudo color or the abnormal color false color, determining that the component estimation value is still an interpolation component value of the pixel point;
- the component estimation value of the pixel point is determined according to formula (2):
- ⁇ c is the preset pseudo color type threshold of component c.
- the interpolation image is subjected to the removal of the pseudo color calculation by re-estimating the component values by estimating the component values at the respective components in the original image according to the pseudo color type.
- the pseudo color type the image pseudo color is suppressed, and the regional pseudo color and the wrong direction false color generated by the interpolation are effectively suppressed, and the accuracy of removing the false color in the interpolated image is ensured.
- the interpolation component of a pixel in the interpolated image is RGB Interpolated
- the original component corresponding to the pixel in the original image is RGB RAW . Since the arrangement of other components in the neighborhood of a certain component of the pixel in the interpolated image array is the same, the following is not limited to a specific interpolated image array.
- the G component of the neighborhood pixel of the R component and the B component pixel is re-evaluated.
- the difference of the G component of the neighborhood pixel is calculated as Gi raw -Gi; where Gi represents the G component of the R component and the nearest neighbor of the B component, and Gi raw represents the G component before the interpolation.
- the G component is not modified
- the threshold ⁇ G can be set according to the noise level of the image sensor, but it should be noted that the noise level is related to the sensor gain. Generally, the threshold ⁇ G is 3 when the sensor gain is 1 under normal illumination intensity.
- estimation method of the component estimation value described above can be used to re-evaluate the R component and the R component in the B component and its neighbors within the neighborhood.
- S204 Determine, according to the component estimation value, a first spatial correlation between the pseudo color interpolation component and the neighborhood interpolation component, and determine, after the pixel interpolation at the first preset component, the interpolation according to the first spatial correlation.
- a second preset component value the pseudo color interpolation component is an interpolation component of a pixel point in the pseudo color image
- the neighborhood interpolation component is an interpolation component of a neighborhood pixel point of the pixel point.
- the first preset component includes an R component or a B component
- the second preset component includes a G component
- the first preset component includes an R component or a B component
- the second preset component includes a B component or an R component.
- step S204 may specifically include S2041 to S2042, as follows:
- the first spatial correlation between the pseudo color interpolation G component and the neighborhood interpolation G component is calculated according to formula (3):
- Gt represents the G component estimation value of the pixel point
- Gi represents the G interpolation component of the neighborhood pixel point
- ⁇ represents a component relationship coefficient
- G1 and G2 represent G component values of the first target pixel
- the first target pixel is obtained by arranging the first spatial correlation from large to small Two neighboring pixel points corresponding to the first spatial correlation.
- the first spatial correlations are sorted in descending order, and the two interpolation components G1 and G2 corresponding to the first and second spatial correlations are selected according to the central pixel points.
- the G component value Gc establishes the relationship between the central pixel point and the two points according to formula (4):
- ⁇ denotes a component relationship coefficient. If the four G component values of the central pixel point do not change when the component estimation value is estimated, the Gc component at the central pixel point remains unchanged. If the component estimation value of the central pixel point estimated in step S201 is changed and changed to one of the two G components nearest to the central pixel point from the re-estimation calculation, the original is re-determined according to formula (5).
- the value of the G component at the R component or the B component is:
- step S204 may specifically include S2043 to S2044, and S2041 to S2042 and S2043 to S2044 are parallel steps.
- the terminal executes S2041 to S2042
- the terminal does not execute S2043 to S2044
- the terminal does not execute S2041 to S2042 when executing S2043 to S2044.
- S2043 ⁇ S2044 are as follows:
- the second preset component further includes a B component or an R component in addition to the G component. Calculating a first spatial correlation between the B component value Cc of the central pixel interpolation and the R component value Ci of the corresponding neighboring pixel point, and the R component value Cc of the central pixel point interpolation and the B of the corresponding neighboring pixel point.
- the first spatial correlation of the component value Ci is:
- ⁇ represents a set of spatial neighborhoods of the interpolated components, ie, a set of four R components or B components that are adjacent to the central pixel point.
- S2044 According to the formula Establishing a second relationship between the pixel point and the second target pixel point, and determining an R component value of the pixel point according to the second relationship; wherein ⁇ represents a component relationship coefficient; R1, R2, and R3 represent The R component value of the second target pixel point; the second target pixel point is a neighboring pixel point corresponding to the first three first spatial correlations obtained by arranging the first spatial correlation from large to small.
- the first spatial correlation is arranged from large to small, taking three pixel points C1, C2, and C3 of the first three first correlations, and establishing a center according to formula (7)
- the relationship between a pixel and the other three points is as follows:
- the spatial correlation between the B component value of the central pixel point interpolation and the R component value of the corresponding neighboring pixel point is And the spatial correlation between the R component value of the central pixel interpolation and the B component value of the corresponding neighboring pixel point can be re-evaluated as follows:
- the right side of the equation is the R component value or the B component value revalued in step S203.
- Estimating the component estimation value of the pixel point by the pseudo color type of the pseudo color according to the image, and re-determining the interpolation of the central pixel point according to the re-estimated component estimation value if the estimated component estimation value changes The spatial correlation between the B component value and the R component value of the corresponding neighboring pixel point, and the spatial correlation between the R component value of the central pixel point interpolation and the B component value of the corresponding neighboring pixel point, suppressing the interpolation result The regional offset at the original component.
- S205 Determine a second spatial correlation between the first component difference and the second component difference according to the second preset component value, and determine the target component according to the second spatial correlation;
- the first component The difference is a difference between a value of a G component after interpolation of a pixel at a green G component in the original image and a value of a red R component;
- the second component difference is a G after interpolation of a pixel at a G component in the original image The difference between the component value and the blue B component value.
- step S205 may specifically include:
- the third relationship determines an R component value at a G component after the pixel interpolation; wherein ⁇ represents a component relationship coefficient; R1 and R2 represent R component values of the third target pixel; G1 and G2 represent the a G component value of the third target pixel; the third target pixel is a neighboring pixel corresponding to the first two second spatial correlations obtained by arranging the second spatial correlation from large to small.
- the second spatial correlation between the first component difference and the second component difference at the central pixel point is calculated according to formula (9) and formula (10):
- ⁇ gr represents a set of four first component differences adjacent to the central pixel point
- j ⁇ gb represents a set of four second component differences adjacent to the central pixel point.
- the central pixel point is the pixel point at the G component in the original image
- the first component difference is the difference between the G component value and the red R component value after the pixel point interpolation at the green G component in the original image
- the component difference is the difference between the G component value and the blue B component value after the pixel point interpolation at the G component in the original image.
- the corresponding pixel point is a third target pixel point
- G1 and G2 are used to represent the G component value of the third target pixel point
- the G component value of the third target pixel point is used to establish a relationship between the central pixel point and the third target pixel point.
- ⁇ gr and ⁇ gb are third relational parameters. It should be noted that since the two points of the first component difference and the second component difference are not necessarily the same, G1 and G2 in the above two equations are not necessarily the same.
- the R component value at the G component is revalued according to the third relationship:
- the value of the B component at the G component is revalued according to the third relationship:
- the quantity on the right side of the equation is the corresponding value after the re-estimation in step S203. This completes the revaluation of the RGB components at each pixel in the image, suppresses the pseudo-color generated by the inaccurate direction estimation during the interpolation, and achieves the suppression of the possible false color.
- the component estimation value at the pixel point is re-estimated according to the pseudo color type, the original component of the original image, and the interpolation component of the interpolation image; and the pseudo color interpolation component is determined according to the component estimation value.
- the component value determines a second spatial correlation between the first component difference and the second component difference, and finally determines the target component based on the second spatial correlation.
- the difference between the original component value in the neighborhood of the central pixel point and the interpolated component value is calculated by the original image data before the interpolation and the interpolated image data, and the mode of the pseudo color is determined, and the component values in the original image are re-evaluated accordingly.
- FIG. 3 is a schematic diagram of an apparatus for suppressing image pseudo color according to an embodiment of the present invention.
- Device 300 can be a device having image processing functionality, including but not limited to a computer, server, tablet, or terminal device. Each unit included in the apparatus 300 of this embodiment is used to perform the steps in the embodiment corresponding to FIG. 1. For details, refer to the related description in the embodiment corresponding to FIG. 1 and FIG. 1 , and details are not described herein.
- the apparatus 300 of the present embodiment includes an image acquisition unit 301, a type determination unit 302, a component determination unit 303, and an image determination unit 304.
- An image obtaining unit 301 configured to acquire an original image and an interpolated image obtained by performing color filter array interpolation on the original image;
- the type determining unit 302 is configured to determine a pseudo color type to which the pseudo color image in the interpolation image belongs;
- a component determining unit 303 configured to determine, at the pixel point in the pseudo color image, according to the pseudo color type, an original component of the original image, an interpolation component of the interpolation image, and a preset image pseudo color suppression policy Target component
- the image determining unit 304 is configured to obtain a pseudo color suppression image according to the target component.
- an interpolated image obtained by acquiring an original image and performing color filter array interpolation on the original image; determining a pseudo color type to which the pseudo color image in the interpolated image belongs; according to the pseudo color type, the original An original component of the image, an interpolation component of the interpolated image, and a preset image pseudo color suppression strategy determine a target component at a pixel point in the pseudo color image; and obtain a pseudo color suppression image according to the target component.
- FIG. 4 is a schematic diagram of an apparatus for suppressing image pseudo color according to an embodiment of the present invention.
- Device 400 can be a device having image processing functionality, including but not limited to a computer, server, tablet, or terminal device. Each unit included in the apparatus 400 of this embodiment is used to perform the steps in the embodiment corresponding to FIG. 2 . For details, refer to the related description in the embodiment corresponding to FIG. 2 and FIG. 2 , and details are not described herein.
- the apparatus 400 of the present embodiment includes an image acquisition unit 401, a type determination unit 402, a pseudo color component estimation unit 403, a preset component calculation unit 404, a target component determination unit 405, and an image determination unit 406.
- An image obtaining unit 401 configured to acquire an original image and an interpolated image obtained by performing color filter array interpolation on the original image
- a type determining unit 402 configured to determine a pseudo color type to which the pseudo color image in the interpolation image belongs
- the pseudo color component estimating unit 403 is configured to re-estimate the component estimation value at the pixel point according to the pseudo color type, the original component of the original image, and the interpolation component of the interpolation image;
- the preset component calculation unit 404 is configured to determine, according to the component estimation value, a first spatial correlation between the pseudo color interpolation component and the neighborhood interpolation component, and determine the first preset component according to the first spatial correlation a second preset component value after the pixel is interpolated;
- the pseudo color interpolation component is an interpolation component of the pixel in the pseudo color image, and the neighborhood interpolation component is a neighboring pixel of the pixel Interpolating component;
- a target component determining unit 405 configured to determine a second spatial correlation between the first component difference and the second component difference according to the second preset component value, and determine the target component according to the second spatial correlation
- the first component difference is a difference between a G component value and a red R component value after pixel point interpolation at a green G component in the original image; the second component difference is at a G component of the original image The difference between the G component value after the pixel interpolation and the blue B component value.
- the image determining unit 406 is configured to obtain a pseudo color suppression image according to the target component.
- the type determining unit 402 specifically includes a component difference calculating unit and a pseudo color type determining unit:
- a component difference calculation unit configured to calculate a difference between the original component in the original image and an interpolation component corresponding to the original component in the interpolation image
- a pseudo color type determining unit configured to determine, according to the difference value, a pseudo color type to which the pseudo color image in the interpolation image belongs.
- component difference calculation unit is specifically used according to the formula Calculating the difference
- Representing the original component Representing an interpolated component corresponding to the original component in the interpolated image, i ⁇ ⁇ , ⁇ representing a spatial neighborhood set of the interpolated component;
- the pseudo color type determining unit is specifically configured to:
- the pseudo color type of the interpolated image is a weak pseudo color
- the pseudo color type of the interpolated image is the same direction pseudo color
- the pseudo color type of the interpolated image is an anomalous pseudo color
- ⁇ c is the preset pseudo color type threshold of component c.
- pseudo color component estimation unit 403 is specifically configured to:
- the pseudo color type is the weak pseudo color or the abnormal color false color, determining that the component estimation value is still an interpolation component value of the pixel point;
- determining an estimated component of the pixel point is:
- the preset component calculation unit 404 is specifically configured to:
- the preset component calculation unit 404 is specifically configured to:
- target component determining unit 405 is specifically configured to:
- the third relationship determines an R component value at a G component after the pixel interpolation; wherein ⁇ represents a component relationship coefficient; R1 and R2 represent R component values of the third target pixel; G1 and G2 represent the a G component value of the third target pixel; the third target pixel is a neighboring pixel corresponding to the first two second spatial correlations obtained by arranging the second spatial correlation from large to small.
- the component estimation value at the pixel point is re-estimated according to the pseudo color type, the original component of the original image, and the interpolation component of the interpolation image; and the pseudo color interpolation component is determined according to the component estimation value.
- the component value determines a second spatial correlation between the first component difference and the second component difference, and finally determines the target component based on the second spatial correlation.
- the difference between the original component value in the neighborhood of the central pixel point and the interpolated component value is calculated by the original image data before the interpolation and the interpolated image data, and the mode of the pseudo color is determined, and the component values in the original image are re-evaluated accordingly.
- FIG. 5 is a schematic diagram of an apparatus for suppressing image pseudo color according to still another embodiment of the present invention.
- the apparatus 500 for suppressing image pseudo color in the present embodiment as shown in FIG. 5 may include a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and operable on the processor 501.
- the processor 501 performs the steps in the method embodiments of the above-described various methods for suppressing image pseudo color when the computer program 503 is executed.
- Memory 502 is for storing a computer program, the program comprising program instructions.
- the processor 501 is configured to execute program instructions stored by the memory 502.
- the processor 501 is configured to invoke the program instruction to perform the following operations:
- a pseudo color suppression image is obtained based on the target component.
- the processor 501 is specifically configured to re-estimate component estimation values at the pixel points according to the pseudo color type, an original component of the original image, and an interpolation component of the interpolation image;
- the processor 501 is specifically configured to:
- the pseudo color interpolation component is an interpolation component of a pixel point in the pseudo color image
- the neighborhood interpolation component is an interpolation component of a neighboring pixel point of the pixel point
- the first component difference is a difference between a G component value after interpolation of a pixel at a green G component in the original image and a red R component value
- the second component difference being a G component value after interpolation of a pixel point at a G component in the original image The difference from the blue B component value.
- the processor 501 is specifically configured to:
- the processor 501 is specifically configured to:
- Representing the original component Representing an interpolated component corresponding to the original component in the interpolated image, i ⁇ ⁇ , ⁇ representing a spatial neighborhood set of the interpolated component;
- the processor 501 is specifically configured to:
- the pseudo color type of the interpolated image is a weak pseudo color
- the pseudo color type of the interpolated image is the same direction pseudo color
- the pseudo color type of the interpolated image is an anomalous pseudo color
- ⁇ c is the preset pseudo color type threshold of component c.
- the processor 501 is specifically configured to:
- the pseudo color type is the weak pseudo color or the abnormal color false color, determining that the component estimation value is still an interpolation component value of the pixel point;
- determining an estimated component of the pixel point is:
- the first preset component includes an R component or a B component; the second preset component includes a G component; and the processor 501 is specifically configured to:
- the first preset component includes an R component or a B component
- the second preset component includes a B component or an R component
- the processor 501 is specifically configured to:
- the processor 501 is specifically configured to:
- the third relationship determines an R component value at a G component after the pixel interpolation; wherein ⁇ represents a component relationship coefficient; R1 and R2 represent R component values of the third target pixel; G1 and G2 represent the a G component value of the third target pixel; the third target pixel is a neighboring pixel corresponding to the first two second spatial correlations obtained by arranging the second spatial correlation from large to small.
- the component estimation value at the pixel point is re-estimated according to the pseudo color type, the original component of the original image, and the interpolation component of the interpolation image; and the pseudo color interpolation component is determined according to the component estimation value.
- the component value determines a second spatial correlation between the first component difference and the second component difference, and finally determines the target component based on the second spatial correlation.
- the difference between the original component value in the neighborhood of the central pixel point and the interpolated component value is calculated by the original image data before the interpolation and the interpolated image data, and the mode of the pseudo color is determined, and the component values in the original image are re-evaluated accordingly.
- the processor 501 may be a central processing unit (CPU), and the processor may also be another general-purpose processor, a digital signal processor (DSP). , Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc.
- the general purpose processor may be a microprocessor or the processor or any conventional processor or the like.
- the memory 502 can include read only memory and random access memory and provides instructions and data to the processor 501.
- a portion of the memory 502 can also include a non-volatile random access memory.
- the memory 502 can also store information of the device type.
- the processor 501, the memory 502, and the computer program 503 described in the embodiments of the present invention may be used in the first embodiment and the second embodiment of the method for pushing the lock screen information provided by the embodiment of the present invention.
- the implementation manner of the terminal described in the embodiment of the present invention may also be implemented in the implementation manner, and details are not described herein again.
- a computer readable storage medium is stored, the computer readable storage medium storing a computer program comprising program instructions, the program instructions being implemented by a processor to:
- a pseudo color suppression image is obtained based on the target component.
- the pseudo color interpolation component is an interpolation component of a pixel point in the pseudo color image
- the neighborhood interpolation component is an interpolation component of a neighboring pixel point of the pixel point
- the first component difference is a difference between a G component value after interpolation of a pixel at a green G component in the original image and a red R component value
- the second component difference being a G component value after interpolation of a pixel point at a G component in the original image The difference from the blue B component value.
- Representing the original component Representing an interpolated component corresponding to the original component in the interpolated image, i ⁇ ⁇ , ⁇ representing a spatial neighborhood set of the interpolated component;
- the pseudo color type of the interpolated image is a weak pseudo color
- the pseudo color type of the interpolated image is the same direction pseudo color
- the pseudo color type of the interpolated image is an anomalous pseudo color
- ⁇ c is the preset pseudo color type threshold of component c.
- the pseudo color type is the weak pseudo color or the abnormal color false color, determining that the component estimation value is still an interpolation component value of the pixel point;
- determining an estimated component of the pixel point is:
- the first preset component includes an R component or a B component; and the second preset component includes a G component;
- the computer program is also implemented when executed by the processor:
- the first preset component includes an R component or a B component
- the second preset component includes a B component or an R component
- the computer program is further executed by the processor to:
- the third relationship determines an R component value at a G component after the pixel interpolation; wherein ⁇ represents a component relationship coefficient; R1 and R2 represent R component values of the third target pixel; G1 and G2 represent the a G component value of the third target pixel; the third target pixel is a neighboring pixel corresponding to the first two second spatial correlations obtained by arranging the second spatial correlation from large to small.
- the component estimation value at the pixel point is re-estimated according to the pseudo color type, the original component of the original image, and the interpolation component of the interpolation image; and the pseudo color interpolation component is determined according to the component estimation value.
- the component value determines a second spatial correlation between the first component difference and the second component difference, and finally determines the target component based on the second spatial correlation.
- the difference between the original component value in the neighborhood of the central pixel point and the interpolated component value is calculated by the original image data before the interpolation and the interpolated image data, and the mode of the pseudo color is determined, and the component values in the original image are re-evaluated accordingly.
- the computer readable storage medium may be an internal storage unit of the terminal described in any of the foregoing embodiments, such as a hard disk or a memory of the terminal.
- the computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk equipped on the terminal, a smart memory card (SMC), and a Secure Digital (SD) card. , Flash Card, etc.
- the computer readable storage medium may also include both an internal storage unit of the terminal and an external storage device.
- the computer readable storage medium is for storing the computer program and other programs and data required by the terminal.
- the computer readable storage medium can also be used to temporarily store data that has been output or is about to be output.
- the disclosed terminal and method may be implemented in other manners.
- the device embodiments described above are merely illustrative.
- the division of the unit is only a logical function division.
- there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
- the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, or an electrical, mechanical or other form of connection.
- the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.
- each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
- the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
- the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
- the technical solution of the present invention contributes in essence or to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium.
- a number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
- the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Processing (AREA)
- Color Television Image Signal Generators (AREA)
- Facsimile Image Signal Circuits (AREA)
Abstract
适用于图像处理技术领域，提供了一种抑制图像伪彩的方法及装置，包括：通过获取原始图像和对原始图像进行颜色滤波阵列插值运算得到的插值图像，确定插值图像中的伪彩图像所属的伪彩类型；根据伪彩类型、原始图像的原始分量、插值图像的插值分量以及预设的图像伪彩抑制策略，确定伪彩图像中的像素点处的目标分量，最后根据目标分量得到伪彩抑制图像。通过插值前的原始图像数据和插值后的图像数据计算中心像素点邻域内的原始分量值和插值后的分量值的差值并判断伪彩的模式，据此重估原始图像中各分量值，通过对插值后的空间相关性进行重新估算，抑制了插值时因方向估计不准确而产生的区域性伪彩和方向错误伪彩，降低了图像的失真度。
Description
本发明属于图像处理技术领域，尤其涉及一种抑制图像伪彩的方法及装置。
通常我们所说的摄像机具有130万像素，指的是有130万个感光点。每一个感光点只能感光红(Red，R)绿(Green,G)蓝(Blue，B)中的一种颜色。但是，要还原一个真正图像，需要每一个点都有RGB三种颜色。因此，将图像中每个像素的像素值当作彩色查找表的表项入口地址，查找对应的RGB强度值进行插值，通过显示插值后的像素颜色以显示真实的图像。但是，在进行图像插值时，很容易由于图像像素点的插值方向估计不准确而产生伪彩。
现有技术中一般进行更准确的边缘估计和合理处理RGB通道间差异，能够减轻伪彩现象，但不能完全消除。特别是场景的纹理过于密集时，不准确的插值方向确定结果将产生色彩错误，也会影响部分图像区域；通过局部平滑方法也无法消除此错误，更大区域的平滑还会模糊图像，因此不能有效抑制图像的区域性伪彩现象，而导致图像显示失真。
有鉴于此，本发明实施例提供了一种抑制图像伪彩的方法及装置，以解决现有技术中不准确的插值方向确定结果产生的色彩错误，而不能有效抑制图像的区域性伪彩现象，导致图像显示失真的问题。
本发明实施例的第一方面提供了一种抑制图像伪彩的方法，包括：
获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；
确定所述插值图像中的伪彩图像所属的伪彩类型；
根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；
根据所述目标分量得到伪彩抑制图像。
本发明实施例的第二方面提供了一种抑制图像伪彩的装置，包括：
图像获取单元，用于获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；
类型确定单元，用于确定所述插值图像中的伪彩图像所属的伪彩类型；
分量确定单元，用于根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；
图像确定单元，用于根据所述目标分量得到伪彩抑制图像。
本发明实施例的第三方面提供了一种抑制图像伪彩的装置，包括：处理器、输入设备、输出设备和存储器，所述处理器、输入设备、输出设备和存储器相互连接，其中，所述存储器用于存储支持装置执行上述方法的计算机程序，所述计算机程序包括程序指令，所述处理器被配置用于调用所述程序指令，执行上述第一方面的方法。
本发明实施例的第四方面提供了一种计算机可读存储介质，所述计算机存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令当被处理器执行时使所述处理器执行上述第一方面的方法。
本发明实施例与现有技术相比存在的有益效果是：通过获取原始图像，对所述原始图像进行颜色滤波阵列插值运算得到插值图像；确定所述插值图像中的伪彩图像所属的伪彩类型；根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量，最后根据所述目标分量得到伪彩抑制图像。通过插值前的原始图像数据和插值后的图像数据计算中心像素点邻域内的原始分量值和插值后的分量值的差值并判断伪彩的模式，据此重估原始图像中各分量值，通过对插值后的空间相关性进行重新估算，抑制了插值时因方向估计不准确而产生的区域性伪彩和方向错误伪彩，降低了图像的失真度。
图1是本发明一实施例提供的抑制图像伪彩的方法的流程图；
图2是本发明另一实施例提供的抑制图像伪彩的方法的流程图；
图3是本发明一实施例提供的抑制图像伪彩的装置的示意图；
图4是本发明另一实施例提供的抑制图像伪彩的装置的示意图；
图5是本发明再一实施例提供的抑制图像伪彩的装置的示意图。
以下描述中，为了说明而不是为了限定，提出了诸如特定系统结构、技术之类的具体细节，以便透彻理解本发明实施例。然而，本邻域的技术人员应当清楚，在没有这些具体细节的其它实施例中也可以实现本发明。在其它情况中，省略对众所周知的系统、装置、电路以及方法的详细说明，以免不必要的细节妨碍本发明的描述。
为了说明本发明所述的技术方案，下面通过具体实施例来进行说明。
实施例1
参见图1，图1是本发明一实施例提供的一种抑制图像伪彩方法的流程图。本实施例中抑制图像伪彩方法的执行主体为具有图像处理功能的装置，包括但不限于计算机、服务器、平板电脑或者终端等装置。如图1所示的抑制图像伪彩方法可以包括以下步骤：
S101：获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像。
现有的图像生成装置利用电子传感器把光学影像转换成电子数据，其中数码相机的传感器是一种光感应式的电荷耦合器件(Charge Coupled Device，CCD)或互补金属氧化物半导体(Complementary Metal Oxide Semiconductor，CMOS)，要获得一幅彩色图像需要三个CCD或者CMOS在每个像素点分别获取红(Red，R)、绿(Green，G)、蓝(Blue，B)三种基本颜色分量。而传感器的价格比较昂贵，为了减小电子产品的体积，降低成本和复杂性，通常仅使用单传感器并在其表面覆盖彩色滤波阵列来同时获得三种基本颜色分量。每一个感光像素之间都有金属隔离层，光线通过显微镜头，在色彩滤波器过滤之后，投射到相应的漏洞式硅的感光元件上。因此，传感器阵列的每个像素点只能采集到一个颜色分量，为了得到一幅全彩色图像，每个像素点必须通过其相邻的已知颜色分量估计出该像素点丢失的另外两种颜色分量。
通过获取原始图像，原始图像中的每一个像素仅仅包括了光谱的一部分，必须通过插值来确定每个像素的RGB值。为了从图像阵列格式得到每个像素的RGB格式，需要通过插值填补缺失的两个色彩。传统的插值方法有：最近邻插值、双线性插值、双平方插值、双立方插值以及其他高阶方法。最近邻插值和双线性插值算法很容易出现锯齿，生成的图片质量不好。因此一般只在对图像质量要求不高的场合下采用。双平方插值和双立方插值在增强图像平滑效果的同时丢失了许多高频信息。而在很多应用场合，细节信息恰恰非常重要，要考虑如何在保证平滑效果的同时尽可能地保留细节信息。
颜色滤波阵列插值通过计算图像三个通道之间的相关系数，以确定每个像素点的颜色分量。颜色滤波阵列插值方法分为启发式和非启发式插值方法。启发式包括边缘方向插值、恒色调插值、高质量线性插值、加权平均插值、模板匹配插值和频域滤波插值等方法；非启发式包括矢量插值、贝叶斯插值、预估计最小平方误差插值方法。
示例性的，边缘方向插值方法中将图像边缘处的模糊确定为由跨边界插值引起的，若能正确判断插值方向，在边界处只沿边界方向而不跨过边界进行插值，则可以提高反马赛克图像质量。通过计算水平垂直梯度，选择梯度小的方向上的相邻信息计算出未知信息；矢量插值方法将像素看作RGB三维空间中的一个矢量，通过对临近像素矢量作差以最小化差向量，实现对所述原始图像进行颜色滤波阵列插值运算得到的插值图像。
S102：确定所述插值图像中的伪彩图像所属的伪彩类型。
由于原始图像在插值之后会出现伪彩现象，通过判断插值图像的伪彩类型，以将该伪彩类型作为处理抑制图像伪彩的一个重要因素。
通过确定原始图像中每个像素点的分量和插值图像的对应分量之间差值，并根据该差值确定目标像素点的邻域像素点的伪彩类型，可以通过该伪彩类型，以根据伪彩类型对原始图像中的像素点进行分量值的估计。
S103：根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像 伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量。
在确定了伪彩类型之后，根据伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量。
通过计算像素点邻域内的原始分量值和插值后的分量值的差值，并根据该差值判断插值图像中各像素点的伪彩类型，据此重估原始图像各像素点处的相应分量的值。建立并增强像素点的邻域像素点插值后的R分量或B分量处的G分量、R分量处的B分量以及B分量处的R分量，并通过这些分量值确定G分量处的G分量与R分量的分量差、G分量与B分量的分量差之间的空间相关度，最后根据空间相关度重估各分量处的目标分量值。本实施例参考了插值前的原始分量值，并对插值后的空间相关性进行重新增强估算，能更好地抑制区域性伪彩和方向错误伪彩。
S104：根据所述目标分量得到伪彩抑制图像。
在根据空间相关度确定了各分量处的目标分量值之后，便可以确定出原始图像中各像素点的分量值，即得到伪彩抑制图像。
上述方案，通过获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；确定所述插值图像中的伪彩图像所属的伪彩类型；根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；根据所述目标分量得到伪彩抑制图像。通过根据插值前的原始分量值，对插值后的空间相关性进行重新增强估算，能更好地抑制区域性伪彩和方向错误伪彩。
实施例2：参见图2，图2是本发明实施例提供的一种抑制图像伪彩方法的流程图。本实施例中抑制图像伪彩方法的执行主体为具有图像处理功能的装置，包括但不限于计算机、服务器、平板电脑或者终端等装置。如图2所示的抑制图像伪彩方法可以包括以下步骤：
S201：获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像。
在本实施例中S201与图1对应的实施例中S101的实现方式完全相同，具体可参考图1对应的实施例中的S101的相关描述，在此不再赘述。
S202：确定所述插值图像中的伪彩图像所属的伪彩类型。
由于原始图像在插值之后会出现伪彩现象，通过判断插值图像的伪彩类型，以将该伪彩类型作为处理抑制图像伪彩的一个重要因素。
通过确定原始图像中每个像素点的分量和插值图像的对应分量之间差值，并根据该差值确定目标像素点的邻域像素点的伪彩类型，可以通过该伪彩类型，以根据伪彩类型对原始图像中的像素点进行分量值的估计。
进一步的，步骤S202可以具体包括S2021～S2022，具体如下：
S2021：计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值。
具体地，在计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值时，根据公式(1)计算该差值：
其中，
表示所述原始图像中的分量值；
表示所述插值图像中与所述原始分量对应的插值分量值，i∈Ω，Ω表示所述插值分量的空间邻域集。
需要说明的是，在3x3的邻域中，插值分量的空间邻域表示图像中与某个像素点相邻的上下左右四个像素点的插值分量，但本实施例中的图像处理仍可在更大的邻域进行，此时，像素点具有大于4个的邻域像素点。
由于原始图像中的每个像素点只有RGB分量中某一个分量，而将原始图像插值之后得到的插值图像中每个像素点都包含R分量、G分量以及B分量，因此，对于原始图像中的某个像素点，这里的差值计算针对的是插值图像中与原始图像中像素点的分量相同的分量。示例性的，原始图像中的某个像素点的分量为G分量，而对该原始图像进行插值之后得到的插值图像中，该像素点处的分量包含R分量、G 分量以及B分量，因此，这里的差值为原始图像中该像素的G分量与插值图像中该像素的G分量的差值。
S2022：根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型。
进一步的，S1022具体包括：
若ΔC
i<ε
c，则所述插值图像的伪彩类型为弱伪彩；
若ΔC
i>ε
c或ΔC
i<-ε
c，则所述插值图像的伪彩类型为同向伪彩；
若ΔC
i>ε
c且ΔC
j<-ε
c，则所述插值图像的伪彩类型为异向伪彩；
其中，ε
c为分量c的预设伪彩类型阈值。
通过确定原始图像中每个像素点的分量和插值图像的对应分量之间差值，并根据该差值确定目标像素点的邻域像素点的伪彩类型，可以通过该伪彩类型，对原始图像中的像素点进行分量值的估计。
S203：根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值。
在确定了伪彩类型之后，根据伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量。
通过计算像素点邻域内的原始分量值和插值后的分量值的差值，并根据该差值判断插值图像中各像素点的伪彩类型，据此重估原始图像各像素点处的相应分量的值。建立并增强像素点的邻域像素点插值后的R分量或B分量处的G分量、R分量处的B分量以及B分量处的R分量，并通过这些分量值确定G分量处的G分量与R分量的分量差、G分量与B分量的分量差之间的空间相关度，最后根据空间相关度重估各分量处的目标分量值。本实施例参考了插值前的原始分量值，并对插值后的空间相关性进行重新增强估算，能更好地抑制区域性伪彩和方向错误伪彩。
进一步的，终端在执行S2022之后，步骤S203可以具体包括：
若所述伪彩类型为所述弱伪彩或所述异向伪彩，则确定所述分量估计值依旧为所述像素点的插值分量值；
若所述伪彩类型为所述同向伪彩，则根据公式(2)确定所述像素点的分量估计值：
其中，ε
c为分量c的预设伪彩类型阈值。
通过根据伪彩类型估计原始图像中的各分量处的分量值，以重新估计的分量值对插值图像进行去除伪彩的计算。并根据伪彩类型抑制图像伪彩，有效抑制插值产生的区域性伪彩及方向错误伪彩，保证在插值图像中去除伪彩的准确性。
示例性的，设插值图像中某一像素点的插值分量为RGB
Interpolated，该像素点对应的在原始图像中的原始分量为RGB
RAW。由于插值图像阵列中像素点的某一分量的邻域内的其他分量的排列相同，因此以下不限于某一具体的插值图像阵列。
可选的，重估R分量和B分量像素点的邻域像素点的G分量。计算邻域像素点的G分量差值为Gi
raw-Gi；其中，Gi表示R分量和B分量最近邻的上下左右四个像素插值后的G分量，Gi
raw表示插值前的G分量。
若对任意i，存在-ε
G<Gi
raw-Gi<ε
G，或对任意i,j，存在Gi
raw-Gi<-ε
G且Gi
raw-Gj>ε
G，则不修改此处G分量值，即G分量值为原始分量值；若对任意i，存在 Gi
raw-Gi<-ε
G或Gi
raw-Gi>ε
G，则重估值为Gi'＝Gi
raw±ε
G。其中，阈值ε
G可根据图像传感器的噪声大小进行设置，但需注意的是噪声大小会和传感器增益相关，一般正常光照强度下传感器增益为1时可取阈值ε
G为3。
需要说明的是，通过上述的分量估计值的估计方式，可以用于重估R分量处及其邻域内的B分量、B分量处及其邻域内的R分量。
S204：根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；所述伪彩插值分量为所述伪彩图像中像素点的插值分量，所述邻域插值分量为所述像素点的邻域像素点的插值分量。
在估计出原始图像中的像素点处的分量估计值之后，根据分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值。其中，第一预设分量包括R分量或B分量，第二预设分量包括G分量；或者，第一预设分量包括R分量或者B分量；所述第二预设分量包括B分量或者R分量。
进一步地，当第一预设分量包括R分量或者B分量；所述第二预设分量包括G分量时，步骤S204可以具体包括S2041～S2042，具体如下：
S2041：通过SCi＝|Gt-Gi|计算伪彩插值G分量与邻域插值G分量之间的第一空间相关度；其中，Gt表示所述像素点的G分量估计值，Gi表示所述邻域像素点的G插值分量。
具体的，根据公式(3)计算伪彩插值G分量与邻域插值G分量之间的第一空间相关度：
SCi＝|Gt-Gi| (3)
其中，Gt表示所述像素点的G分量估计值，Gi表示所述邻域像素点的G插值分量。
S2042：根据公式(Gt-G1)＝α(G2-G1)建立所述像素点与第一目标像素点之间的第一关系，并根据所述第一关系确定所述像素点的G分量值；其中，α表示分量关系系数；G1和G2表示所述第一目标像素点的G分量值；所述第一目标像素点是将所述第一空间相关度从大到小排列所得到的前两个第一空间相关度对应的邻域像素点。
在计算出第一空间相关度之后，对第一空间相关度按照从大到小的顺序排序，选择第一个和第二个空间相关度对应的两个插值分量G1和G2，根据中心像素点的G分量值Gc，根据公式(4)建立中心像素点和此两个点的关系：
(Gc-G1)＝α(G2-G1) (4)
其中，α表示分量关系系数。若在估计分量估计值时中心像素点四个G分量值均未变化，则中心像素点处的Gc分量亦保持不变。若在步骤S201中所估计出来的中心像素点的分量估计值发生改变，且改变为从重估计算中与中心像素点最近邻的两个G分量之一，则根据公式(5)重新确定原R分量或B分量处的G分量值为：
Gc'＝G1'+α(G2'+G1') (5)
其中等式右边的量均为经重估后的值。
进一步地，当第一预设分量包括R分量或者B分量；所述第二预设分量包括B分量或者R分量时，步骤S204可以具体包括S2043～S2044，S2041～S2042与S2043～S2044是并列步骤，终端在执行S2041～S2042时不执行S2043～S2044，终端在执行S2043～S2044时不执行S2041～S2042。S2043～S2044具体如下：
S2043：通过SCi＝|Rt-Ri|计算伪彩插值R分量与邻域插值R分量之间的第一空间相关度；其 中，Rt表示所述像素点的R分量估计值，Ri表示所述邻域像素点的R插值分量。
具体的，第二预设分量在G分量之外还包括B分量或R分量。计算中心像素点插值后的B分量值Cc与其对应的邻域像素点的R分量值Ci的第一空间相关度，以及中心像素点插值后的R分量值Cc与其对应的邻域像素点的B分量值Ci的第一空间相关度为：
SCi＝|Cc-Ci| (6)
其中，i∈Ω，Ω表示所述插值分量的空间邻域集，即与中心像素点相近邻的四个R分量或B分量的集合。
S2044：根据公式
建立所述像素点与第二目标像素点之间的第二关系，并根据所述第二关系确定所述像素点的R分量值；其中，β表示分量关系系数；R1、R2和R3表示所述第二目标像素点的R分量值；所述第二目标像素点是将所述第一空间相关度从大到小排列所得到的前三个第一空间相关度对应的邻域像素点。
在计算出第一空间相关度之后，将所述第一空间相关度从大到小排列，取前三个第一相关度的三个像素点C1、C2和C3，根据公式(7)建立中心像素点和其他三个点的关系如下：
若在步骤S203中所估计出来的相关度最大的三个点的分量估计值有被重估，中心像素点插值后的B分量值与其对应的邻域像素点的R分量值的空间相关度，以及中心像素点插值后的R分量值与其对应的邻域像素点的B分量值的空间相关度可重估如下：
其中等式右边均为步骤S203重估后的R分量值或B分量值。通过根据图像发生伪彩的伪彩类型，估计像素点的分量估计值，并在所估计出来的分量估计值发生变化的情况下，根据重新估计出来的分量估计值重新确定中心像素点插值后的B分量值与其对应的邻域像素点的R分量值的空间相关度，以及中心像素点插值后的R分量值与其对应的邻域像素点的B分量值的空间相关度，抑制因插值导致的原始分量处的区域性偏移。
S205：根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量；所述第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；所述第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
在根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值之后，根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量。
进一步地，步骤S205可以具体包括：
通过SCi＝|(Gt-Rt)-(Gi-Ri)|计算所述第二空间相关度；
根据公式((Gt-Rt)-(G1-R1))＝γ((G2-R2)-(G1-R1))建立所述像素点与第三目标像素点之间的第三关系，并根据所述第三关系确定所述像素点插值后G分量处的R分量值；其中，γ表示分量关系系数；R1和R2表示所述第三目标像素点的R分量值；G1和G2表示所述第三目标像素点的G分量值；所述第三目标像素点是将所述第二空间相关度从大到小排列所得到的前两个第二空间相关度对应的邻域像素点。
具体的，根据公式(9)和公式(10)计算中心像素点处的第一分量差与第二分量差之间的第二空间相关度：
SCi＝|(Gc-Rc)-(Gi-Ri)| (9)
SCj＝|(Gc-Bc)-(Gj-Bj)| (10)
其中，i∈Ωgr，Ωgr表示与中心像素点相邻的四个第一分量差的集合；j∈Ωgb，Ωgb表示与中心像素点相邻的四个第二分量差的集合。
其中，中心像素点即为原始图像中G分量处的像素点，第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度之后，将第二空间相关度从大到小排列，取前两个第二空间相关度对应的像素点为第三目标像素点，用G1和G2表示第三目标像素点的G分量值，根据第三目标像素点的G分量值建立中心像素点与第三目标像素点之间的第三关系为公式(11)和公式(12)：
((Gc-Rc)-(G1-R1))＝γ
gr((G2-R2)-(G1-R1)) (11)
((Gc-Bc)-(G1-B1))＝γ
gb((G2-B2)-(G1-B1)) (12)
其中，γ
gr及γ
gb为第三关系参数。需要说明的是，由于第一分量差和第二分量差的最相关的两个点不必相同，因此上述两式中的G1和G2也不必相同。
在建立了中心像素点与第三目标像素点之间的第三关系之后，根据该第三关系重估G分量处的R分量值为：
Rc'＝Gc'-((G1'-R1')+γ
gr((G2'-R2')-(G1'-R1'))) (13)
根据该第三关系重估G分量处的B分量值为：
Bc'＝Gc'
-((G1'-B1')+γ
gb((G2'-B2')-(G1'-B1'))) (14)
其中，若在步骤S203中所估计出来的相关度最大的三个点的分量估计值有被重估或者修改，则等式右边的量均为经过步骤S203重估后的对应的值。至此完成对图像中每个像素点处的RGB各分量的重估，抑制插值时因方向估计不准确产生的伪彩，实现对可能存在的伪彩的抑制。
S206：根据所述目标分量得到伪彩抑制图像。
在本实施例中S206与图1对应的实施例中S104的实现方式完全相同，具体可参考图1对应的实施例中的S104的相关描述，在此不再赘述。
上述方案，通过根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，最后根据所述第二空间相关度确定所述目标分量。通过插值前的原始图像数据和插值后的图像数据计算中心像素点邻域内的原始分量值和插值后的分量值的差值并判断伪彩的模式，据此重估原始图像中各分量值，通过对插值后的空间相关性进行重新估算，抑制了插值时因方向估计不准确而产生的区域性伪彩和方向错误伪彩，降低了图像的失真度。
实施例3：参见图3，图3是本发明实施例提供的一种抑制图像伪彩的装置的示意图。装置300可以为具有图像处理功能的装置，包括但不限于计算机、服务器、平板电脑或者终端等装置。本实施例的装置300包括的各单元用于执行图1对应的实施例中的各步骤，具体请参阅图1及图1对应的实施例中的相关描述，此处不赘述。本实施例的装置300包括图像获取单元301、类型确定单元302、分量确定单元 303以及图像确定单元304。
图像获取单元301，用于获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；
类型确定单元302，用于确定所述插值图像中的伪彩图像所属的伪彩类型；
分量确定单元303，用于根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；
图像确定单元304，用于根据所述目标分量得到伪彩抑制图像。
上述方案，通过获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；确定所述插值图像中的伪彩图像所属的伪彩类型；根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；根据所述目标分量得到伪彩抑制图像。通过根据插值前的原始分量值，对插值后的空间相关性进行重新增强估算，能更好地抑制区域性伪彩和方向错误伪彩。
实施例4：参见图4，图4是本发明实施例提供的一种抑制图像伪彩的装置的示意图。装置400可以为具有图像处理功能的装置，包括但不限于计算机、服务器、平板电脑或者终端等装置。本实施例的装置400包括的各单元用于执行图2对应的实施例中的各步骤，具体请参阅图2及图2对应的实施例中的相关描述，此处不赘述。本实施例的装置400包括图像获取单元401、类型确定单元402、伪彩分量估计单元403、预设分量计算单元404、目标分量确定单元405以及图像确定单元406。
图像获取单元401，用于获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；
类型确定单元402，用于确定所述插值图像中的伪彩图像所属的伪彩类型；
伪彩分量估计单元403，用于根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；
预设分量计算单元404，用于根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；所述伪彩插值分量为所述伪彩图像中像素点的插值分量，所述邻域插值分量为所述像素点的邻域像素点的插值分量；
目标分量确定单元405，用于根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量；所述第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；所述第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
图像确定单元406，用于根据所述目标分量得到伪彩抑制图像。
进一步地，类型确定单元402具体包括分量差值计算单元和伪彩类型确定单元：
分量差值计算单元，用于计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值；
伪彩类型确定单元，用于根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型。
进一步的，分量差值计算单元具体用于根据公式
计算所述差值；
其中，
表示所述原始分量；
表示所述插值图像中与所述原始分量对应的插值分量，i∈Ω，Ω表示所述插值分量的空间邻域集；
进一步的，伪彩类型确定单元具体用于：
若ΔC
i<ε
c，则所述插值图像的伪彩类型为弱伪彩；
若ΔC
i>ε
c或ΔC
i<-ε
c，则所述插值图像的伪彩类型为同向伪彩；
若ΔC
i>ε
c且ΔC
j<-ε
c，则所述插值图像的伪彩类型为异向伪彩；
其中，ε
c为分量c的预设伪彩类型阈值。
进一步的，伪彩分量估计单元403具体用于：
若所述伪彩类型为所述弱伪彩或所述异向伪彩，则确定所述分量估计值依旧为所述像素点的插值分量值；
若所述伪彩类型为所述同向伪彩，则确定所述像素点的分量估计值为：
进一步地，当第一预设分量包括R分量或者B分量，所述第二预设分量包括G分量时，预设分量计算单元404具体用于：
通过SCi＝|Gt-Gi|计算伪彩插值G分量与邻域插值G分量之间的第一空间相关度；其中，Gt表示所述像素点的G分量估计值，Gi表示所述邻域像素点的G插值分量；
根据公式(Gt-G1)＝α(G2-G1)建立所述像素点与第一目标像素点之间的第一关系，并根据所述第一关系确定所述像素点的G分量值；其中，α表示分量关系系数；G1和G2表示所述第一目标像素点的G分量值；所述第一目标像素点是将所述第一空间相关度从大到小排列所得到的前两个第一空间相关度对应的邻域像素点。
进一步地，当第一预设分量包括R分量或者B分量；所述第二预设分量包括B分量或者R分量时，预设分量计算单元404具体用于：
通过SCi＝|Rt-Ri|计算伪彩插值R分量与邻域插值R分量之间的第一空间相关度；其中，Rt表示所述像素点的R分量估计值，Ri表示所述邻域像素点的R插值分量；
根据公式
建立所述像素点与第二目标像素点之间的第二关系，并根据所述第二关系确定所述像素点的R分量值；其中，β表示分量关系系数；R1、R2和R3表示所述第二目标像素点的R分量值；所述第二目标像素点是将所述第一空间相关度从大到小排列所得到的前三个第一空间相关度对应的邻域像素点。
进一步地，目标分量确定单元405具体用于：
通过SCi＝|(Gt-Rt)-(Gi-Ri)|计算所述第二空间相关度；
根据公式((Gt-Rt)-(G1-R1))＝γ((G2-R2)-(G1-R1))建立所述像素点与第三目标像素点之间的第三关系，并根据所述第三关系确定所述像素点插值后G分量处的R分量值；其中，γ表示分量关系系数；R1和R2表示所述第三目标像素点的R分量值；G1和G2表示所述第三目标像素点的G分量值；所述第三目标像素点是将所述第二空间相关度从大到小排列所得到的前两个第二空间相关度对应的邻域像素点。
上述方案，通过根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，最后根据所述第二空间相关度确定所述目标分量。通过插值前的原始图像数据和插值后的图像数据计算中心像素点邻域内的原始分量值和插值后的分量值的差值并判断伪彩的模式，据此重估原始图像中各分量值，通过对插值后的空间相关性进行重新估算，抑制了插值时因方向估计不准确而产生的区域性伪彩和方向错误伪彩，降低了图像的失真度。
应理解，上述实施例中各步骤的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本发明实施例的实施过程构成任何限定。
实施例5：参见图5，图5是本发明再一实施例提供的一种抑制图像伪彩的装置的示意图。如图5所示的本实施例中的抑制图像伪彩的装置500可以包括：处理器501、存储器502以及存储在存储器502中 并可在处理器501上运行的计算机程序503。处理器501执行计算机程序503时实现上述各个抑制图像伪彩的方法实施例中的步骤。存储器502用于存储计算机程序，所述计算机程序包括程序指令。处理器501用于执行存储器502存储的程序指令。其中，处理器501被配置用于调用所述程序指令执行以下操作：
获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；
确定所述插值图像中的伪彩图像所属的伪彩类型；
根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；
根据所述目标分量得到伪彩抑制图像。
可选地，处理器501具体用于根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；
可选地，处理器501具体用于：
根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；所述伪彩插值分量为所述伪彩图像中像素点的插值分量，所述邻域插值分量为所述像素点的邻域像素点的插值分量；
根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量；所述第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；所述第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
可选地，处理器501具体用于：
计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值；
根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型。
可选地，处理器501具体用于：
根据公式
计算所述差值；
其中，
表示所述原始分量；
表示所述插值图像中与所述原始分量对应的插值分量，i∈Ω，Ω表示所述插值分量的空间邻域集；
可选地，处理器501具体用于：
根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型，具体的：
若ΔC
i<ε
c，则所述插值图像的伪彩类型为弱伪彩；
若ΔC
i>ε
c或ΔC
i<-ε
c，则所述插值图像的伪彩类型为同向伪彩；
若ΔC
i>ε
c且ΔC
j<-ε
c，则所述插值图像的伪彩类型为异向伪彩；
其中，ε
c为分量c的预设伪彩类型阈值。
可选地，处理器501具体用于：
若所述伪彩类型为所述弱伪彩或所述异向伪彩，则确定所述分量估计值依旧为所述像素点的插值分量值；
若所述伪彩类型为所述同向伪彩，则确定所述像素点的分量估计值为：
可选地，所述第一预设分量包括R分量或者B分量；所述第二预设分量包括G分量；处理器501具体用于：
通过SCi＝|Gt-Gi|计算伪彩插值G分量与邻域插值G分量之间的第一空间相关度；其中，Gt表 示所述像素点的G分量估计值，Gi表示所述邻域像素点的G插值分量；
根据公式(Gt-G1)＝α(G2-G1)建立所述像素点与第一目标像素点之间的第一关系，并根据所述第一关系确定所述像素点的G分量值；其中，α表示分量关系系数；G1和G2表示所述第一目标像素点的G分量值；所述第一目标像素点是将所述第一空间相关度从大到小排列所得到的前两个第一空间相关度对应的邻域像素点。
可选地，所述第一预设分量包括R分量或者B分量；所述第二预设分量包括B分量或者R分量；处理器501具体用于：
通过SCi＝|Rt-Ri|计算伪彩插值R分量与邻域插值R分量之间的第一空间相关度；其中，Rt表示所述像素点的R分量估计值，Ri表示所述邻域像素点的R插值分量；
根据公式
建立所述像素点与第二目标像素点之间的第二关系，并根据所述第二关系确定所述像素点的R分量值；其中，β表示分量关系系数；R1、R2和R3表示所述第二目标像素点的R分量值；所述第二目标像素点是将所述第一空间相关度从大到小排列所得到的前三个第一空间相关度对应的邻域像素点。
可选地，处理器501具体用于：
通过SCi＝|(Gt-Rt)-(Gi-Ri)|计算所述第二空间相关度；
根据公式((Gt-Rt)-(G1-R1))＝γ((G2-R2)-(G1-R1))建立所述像素点与第三目标像素点之间的第三关系，并根据所述第三关系确定所述像素点插值后G分量处的R分量值；其中，γ表示分量关系系数；R1和R2表示所述第三目标像素点的R分量值；G1和G2表示所述第三目标像素点的G分量值；所述第三目标像素点是将所述第二空间相关度从大到小排列所得到的前两个第二空间相关度对应的邻域像素点。
上述方案，通过根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，最后根据所述第二空间相关度确定所述目标分量。通过插值前的原始图像数据和插值后的图像数据计算中心像素点邻域内的原始分量值和插值后的分量值的差值并判断伪彩的模式，据此重估原始图像中各分量值，通过对插值后的空间相关性进行重新估算，抑制了插值时因方向估计不准确而产生的区域性伪彩和方向错误伪彩，降低了图像的失真度。
应当理解，在本发明实施例中，所称处理器501可以是中央处理单元(Central Processing Unit，CPU)，该处理器还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
该存储器502可以包括只读存储器和随机存取存储器，并向处理器501提供指令和数据。存储器502的一部分还可以包括非易失性随机存取存储器。例如，存储器502还可以存储设备类型的信息。
具体实现中，本发明实施例中所描述的处理器501、存储器502、计算机程序503可执行本发明实施例提供的推送锁屏信息的方法的第一实施例和第二实施例中所描述的实现方式，也可执行本发明实施例所描述的终端的实现方式，在此不再赘述。
在本发明的另一实施例中提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令被处理器执行时实现：
获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；
确定所述插值图像中的伪彩图像所属的伪彩类型；
根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；
根据所述目标分量得到伪彩抑制图像。
进一步的，所述计算机程序被处理器执行时还实现：
根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；
根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；所述伪彩插值分量为所述伪彩图像中像素点的插值分量，所述邻域插值分量为所述像素点的邻域像素点的插值分量；
根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量；所述第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；所述第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
进一步的，所述计算机程序被处理器执行时还实现：
计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值；
根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型。
进一步的，所述计算机程序被处理器执行时还实现：
根据公式
计算所述差值；
其中，
表示所述原始分量；
表示所述插值图像中与所述原始分量对应的插值分量，i∈Ω，Ω表示所述插值分量的空间邻域集；
进一步的，所述计算机程序被处理器执行时还实现：
根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型，具体的：
若ΔC
i<ε
c，则所述插值图像的伪彩类型为弱伪彩；
若ΔC
i>ε
c或ΔC
i<-ε
c，则所述插值图像的伪彩类型为同向伪彩；
若ΔC
i>ε
c且ΔC
j<-ε
c，则所述插值图像的伪彩类型为异向伪彩；
其中，ε
c为分量c的预设伪彩类型阈值。
进一步的，所述计算机程序被处理器执行时还实现：
若所述伪彩类型为所述弱伪彩或所述异向伪彩，则确定所述分量估计值依旧为所述像素点的插值分量值；
若所述伪彩类型为所述同向伪彩，则确定所述像素点的分量估计值为：
进一步的，所述第一预设分量包括R分量或者B分量；所述第二预设分量包括G分量；
所述计算机程序被处理器执行时还实现：
通过SCi＝|Gt-Gi|计算伪彩插值G分量与邻域插值G分量之间的第一空间相关度；其中，Gt表示所述像素点的G分量估计值，Gi表示所述邻域像素点的G插值分量；
根据公式(Gt-G1)＝α(G2-G1)建立所述像素点与第一目标像素点之间的第一关系，并根据所述第一关系确定所述像素点的G分量值；其中，α表示分量关系系数；G1和G2表示所述第一目标像 素点的G分量值；所述第一目标像素点是将所述第一空间相关度从大到小排列所得到的前两个第一空间相关度对应的邻域像素点。
进一步的，所述第一预设分量包括R分量或者B分量；所述第二预设分量包括B分量或者R分量；所述计算机程序被处理器执行时还实现：
通过SCi＝|Rt-Ri|计算伪彩插值R分量与邻域插值R分量之间的第一空间相关度；其中，Rt表示所述像素点的R分量估计值，Ri表示所述邻域像素点的R插值分量；
根据公式
建立所述像素点与第二目标像素点之间的第二关系，并根据所述第二关系确定所述像素点的R分量值；其中，β表示分量关系系数；R1、R2和R3表示所述第二目标像素点的R分量值；所述第二目标像素点是将所述第一空间相关度从大到小排列所得到的前三个第一空间相关度对应的邻域像素点。
进一步的，所述计算机程序被处理器执行时还实现：
通过SCi＝|(Gt-Rt)-(Gi-Ri)|计算所述第二空间相关度；
根据公式((Gt-Rt)-(G1-R1))＝γ((G2-R2)-(G1-R1))建立所述像素点与第三目标像素点之间的第三关系，并根据所述第三关系确定所述像素点插值后G分量处的R分量值；其中，γ表示分量关系系数；R1和R2表示所述第三目标像素点的R分量值；G1和G2表示所述第三目标像素点的G分量值；所述第三目标像素点是将所述第二空间相关度从大到小排列所得到的前两个第二空间相关度对应的邻域像素点。
上述方案，通过根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，最后根据所述第二空间相关度确定所述目标分量。通过插值前的原始图像数据和插值后的图像数据计算中心像素点邻域内的原始分量值和插值后的分量值的差值并判断伪彩的模式，据此重估原始图像中各分量值，通过对插值后的空间相关性进行重新估算，抑制了插值时因方向估计不准确而产生的区域性伪彩和方向错误伪彩，降低了图像的失真度。
所述计算机可读存储介质可以是前述任一实施例所述的终端的内部存储单元，例如终端的硬盘或内存。所述计算机可读存储介质也可以是所述终端的外部存储设备，例如所述终端上配备的插接式硬盘，智能存储卡(Smart Media Card，SMC)，安全数字(Secure Digital，SD)卡，闪存卡(Flash Card)等。进一步地，所述计算机可读存储介质还可以既包括所述终端的内部存储单元也包括外部存储设备。所述计算机可读存储介质用于存储所述计算机程序及所述终端所需的其他程序和数据。所述计算机可读存储介质还可以用于暂时地存储已经输出或者将要输出的数据。
本邻域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明的范围。
所属邻域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的终端和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的终端和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些 特征可以忽略，或不执行。另外，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口、装置或单元的间接耦合或通信连接，也可以是电的，机械的或其它的形式连接。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本发明实施例方案目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以是两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分，或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术邻域的技术人员在本发明揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以权利要求的保护范围为准。
Claims (13)
- 一种抑制图像伪彩的方法，其特征在于，包括：获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；确定所述插值图像中的伪彩图像所属的伪彩类型；根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；根据所述目标分量得到伪彩抑制图像。
- 如权利要求1所述的抑制图像伪彩的方法，其特征在于，所述根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩类型对应的图像区域中的像素点处的目标分量，包括：根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；所述伪彩插值分量为所述伪彩图像中像素点的插值分量，所述邻域插值分量为所述像素点的邻域像素点的插值分量；根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量；所述第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；所述第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
- 如权利要求1或2所述的抑制图像伪彩的方法，其特征在于，所述确定所述插值图像中的伪彩图像所属的伪彩类型，包括：计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值；根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型。
- 如权利要求3所述的抑制图像伪彩的方法，其特征在于，所述计算所述原始图像中所述原始分量与所述插值图像中与所述原始分量对应的插值分量的差值，包括：根据公式计算所述差值；
其中，表示所述原始分量；
表示所述插值图像中与所述原始分量对应的插值分量，i∈Ω，Ω表示所述插值分量的空间邻域集；
所述根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型，包括：若ΔC i<ε c，则所述插值图像的伪彩类型为弱伪彩；若ΔC i>ε c或ΔC i<-ε c，则所述插值图像的伪彩类型为同向伪彩；若ΔC i>ε c且ΔC j<-ε c，则所述插值图像的伪彩类型为异向伪彩；其中，ε c为分量c的预设伪彩类型阈值。 - 如权利要求4所述的抑制图像伪彩的方法，其特征在于，所述根据所述伪彩类型、所述原始分量和所述插值分量重新估计所述像素点处的分量估计值，包括：若所述伪彩类型为所述弱伪彩或所述异向伪彩，则确定所述分量估计值依旧为所述像素点的插值分量值；若所述伪彩类型为所述同向伪彩，则确定所述像素点的分量估计值为：
- 如权利要求5所述的抑制图像伪彩的方法，其特征在于，所述第一预设分量包括R分量或者B分量；所述第二预设分量包括G分量；所述根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值，包括：通过SCi＝|Gt-Gi|计算伪彩插值G分量与邻域插值G分量之间的第一空间相关度；其中，Gt表示所述像素点的G分量估计值，Gi表示所述邻域像素点的G插值分量；根据公式(Gt-G1)＝α(G2-G1)建立所述像素点与第一目标像素点之间的第一关系，并根据所述第一关系确定所述像素点的G分量值；其中，α表示分量关系系数；G1和G2表示所述第一目标像素点的G分量值；所述第一目标像素点是将所述第一空间相关度从大到小排列所得到的前两个第一空间相关度对应的邻域像素点。
- 如权利要求5所述的抑制图像伪彩的方法，其特征在于，所述第一预设分量包括R分量或者B分量；所述第二预设分量包括B分量或者R分量；所述根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值，包括：通过SCi＝|Rt-Ri|计算伪彩插值R分量与邻域插值R分量之间的第一空间相关度；其中，Rt表示所述像素点的R分量估计值，Ri表示所述邻域像素点的R插值分量；根据公式建立所述像素点与第二目标像素点之间的第二关系，并根据所述第二关系确定所述像素点的R分量值；其中，β表示分量关系系数；R1、R2和R3表示所述第二目标像素点的R分量值；所述第二目标像素点是将所述第一空间相关度从大到小排列所得到的前三个第一空间相关度对应的邻域像素点。
- 如权利要求6或7所述的抑制图像伪彩的方法，其特征在于，所述根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量，包括：通过SCi＝|(Gt-Rt)-(Gi-Ri)|计算所述第二空间相关度；根据公式((Gt-Rt)-(G1-R1))＝γ((G2-R2)-(G1-R1))建立所述像素点与第三目标像素点之间的第三关系，并根据所述第三关系确定所述像素点插值后G分量处的R分量值；其中，γ表示分量关系系数；R1和R2表示所述第三目标像素点的R分量值，Rt表示所述像素点的R分量估计值；G1和G2表示所述第三目标像素点的G分量值，Gt表示所述像素点的G分量估计值；所述第三目标像素点是将所述第二空间相关度从大到小排列所得到的前两个第二空间相关度对应的邻域像素点。
- 一种抑制图像伪彩的装置，其特征在于，包括：图像获取单元，用于获取原始图像和对所述原始图像进行颜色滤波阵列插值运算得到的插值图像；类型确定单元，用于确定所述插值图像中的伪彩图像所属的伪彩类型；分量确定单元，用于根据所述伪彩类型、所述原始图像的原始分量、所述插值图像的插值分量以及预设的图像伪彩抑制策略，确定所述伪彩图像中的像素点处的目标分量；图像确定单元，用于根据所述目标分量得到伪彩抑制图像。
- 如权利要求9所述的抑制图像伪彩的装置，其特征在于，所述分量确定单元包括：伪彩分量估计单元，用于根据所述伪彩类型、所述原始图像的原始分量和所述插值图像的插值分量重新估计所述像素点处的分量估计值；预设分量计算单元，用于根据所述分量估计值，确定伪彩插值分量与邻域插值分量之间的第一空 间相关度，并根据所述第一空间相关度确定第一预设分量处的像素点插值后的第二预设分量值；所述伪彩插值分量为所述伪彩图像中像素点的插值分量，所述邻域插值分量为所述像素点的邻域像素点的插值分量；目标分量确定单元，用于根据所述第二预设分量值确定第一分量差与第二分量差之间的第二空间相关度，并根据所述第二空间相关度确定所述目标分量；所述第一分量差为所述原始图像中绿色G分量处的像素点插值之后的G分量值与红色R分量值之差；所述第二分量差为所述原始图像中G分量处的像素点插值之后的G分量值与蓝色B分量值之差。
- 如权利要求10所述的抑制图像伪彩的装置，其特征在于，所述类型确定单元包括：分量差值计算单元，用于计算所述原始图像中所述原始分量与所述插值图像中所述原始分量对应的插值分量的差值；伪彩类型确定单元，用于根据所述差值确定所述插值图像中的伪彩图像所属的伪彩类型。
- 一种抑制图像伪彩的装置，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如权利要求1至8任一项所述方法的步骤。
- 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至8任一项所述方法的步骤。
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201880000289.3A CN108701353B (zh) | 2018-04-13 | 2018-04-13 | 一种抑制图像伪彩的方法及装置 |
| PCT/CN2018/083035 WO2019196109A1 (zh) | 2018-04-13 | 2018-04-13 | 一种抑制图像伪彩的方法及装置 |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/083035 WO2019196109A1 (zh) | 2018-04-13 | 2018-04-13 | 一种抑制图像伪彩的方法及装置 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2019196109A1 true WO2019196109A1 (zh) | 2019-10-17 |
Family
ID=63841473
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2018/083035 WO2019196109A1 (zh) | 2018-04-13 | 2018-04-13 | 一种抑制图像伪彩的方法及装置 |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN108701353B (zh) |
| WO (1) | WO2019196109A1 (zh) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116342401A (zh) * | 2022-09-06 | 2023-06-27 | 上海玄戒技术有限公司 | 一种图像处理方法、装置、电子设备、芯片及存储介质 |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111028198B (zh) * | 2019-07-12 | 2024-02-23 | 北京达佳互联信息技术有限公司 | 图像质量评估方法、装置、终端及可读存储介质 |
| CN112652027B (zh) * | 2020-12-30 | 2024-03-22 | 凌云光技术股份有限公司 | 一种伪彩检测方法及系统 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101399996A (zh) * | 2007-09-27 | 2009-04-01 | 比亚迪股份有限公司 | 一种彩色滤镜阵列插值方法 |
| US20110158512A1 (en) * | 2009-12-31 | 2011-06-30 | Industrial Technology Research Institute | Method and System for Developing New-View Image |
| CN102665030A (zh) * | 2012-05-14 | 2012-09-12 | 浙江大学 | 一种基于改进双线性的Bayer格式颜色插值方法 |
| CN106303483A (zh) * | 2015-05-20 | 2017-01-04 | 浙江大华技术股份有限公司 | 一种图像处理方法及装置 |
| CN106507066A (zh) * | 2016-11-22 | 2017-03-15 | 深圳艾科创新微电子有限公司 | 抑制图像伪彩色的方法、装置 |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101827273B (zh) * | 2009-03-02 | 2013-03-20 | 华晶科技股份有限公司 | 图像的色彩重现方法 |
| CN101917629B (zh) * | 2010-08-10 | 2012-03-07 | 浙江大学 | 一种基于绿色分量和色差空间的Bayer格式颜色插值方法 |
| JP6056659B2 (ja) * | 2013-05-30 | 2017-01-11 | 株式会社Ｊｖｃケンウッド | 映像信号処理装置及び方法 |
| CN103595981B (zh) * | 2013-10-25 | 2015-09-30 | 西安电子科技大学 | 基于非局部低秩的色彩滤波阵列图像去马赛克方法 |
| CN104537625A (zh) * | 2015-01-05 | 2015-04-22 | 中国科学院光电技术研究所 | 一种基于方向标志位的Bayer彩色图像插值方法 |
| US9674466B2 (en) * | 2015-02-26 | 2017-06-06 | Dual Aperture International Co., Ltd. | Hybrid image correction for dual-aperture camera |
| CN106303474A (zh) * | 2016-09-29 | 2017-01-04 | 杭州雄迈集成电路技术有限公司 | 一种基于g模式色彩滤波阵列的去马赛克方法及装置 |
-
2018
- 2018-04-13 WO PCT/CN2018/083035 patent/WO2019196109A1/zh active Application Filing
- 2018-04-13 CN CN201880000289.3A patent/CN108701353B/zh active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101399996A (zh) * | 2007-09-27 | 2009-04-01 | 比亚迪股份有限公司 | 一种彩色滤镜阵列插值方法 |
| US20110158512A1 (en) * | 2009-12-31 | 2011-06-30 | Industrial Technology Research Institute | Method and System for Developing New-View Image |
| CN102665030A (zh) * | 2012-05-14 | 2012-09-12 | 浙江大学 | 一种基于改进双线性的Bayer格式颜色插值方法 |
| CN106303483A (zh) * | 2015-05-20 | 2017-01-04 | 浙江大华技术股份有限公司 | 一种图像处理方法及装置 |
| CN106507066A (zh) * | 2016-11-22 | 2017-03-15 | 深圳艾科创新微电子有限公司 | 抑制图像伪彩色的方法、装置 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116342401A (zh) * | 2022-09-06 | 2023-06-27 | 上海玄戒技术有限公司 | 一种图像处理方法、装置、电子设备、芯片及存储介质 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108701353B (zh) | 2021-12-10 |
| CN108701353A (zh) | 2018-10-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9654700B2 (en) | Computational camera using fusion of image sensors | |
| US9344639B2 (en) | High dynamic range array camera | |
| JP5260635B2 (ja) | パンクロマチック画像を用いたノイズ低減されたカラーの画像 | |
| US7844127B2 (en) | Edge mapping using panchromatic pixels | |
| US20080253652A1 (en) | Method of demosaicing a digital mosaiced image | |
| KR101183371B1 (ko) | 디지털 컬러 이미지 처리 방법 | |
| JP5672776B2 (ja) | 画像処理装置、および画像処理方法、並びにプログラム | |
| US20110243428A1 (en) | Bi-Affinity Filter: A Bilateral Type Filter for Color Images | |
| US8284271B2 (en) | Chroma noise reduction for cameras | |
| KR100667803B1 (ko) | 컬러 채널 상호간의 특성을 고려한 컬러 잡음 제거 방법 및장치 | |
| KR101389562B1 (ko) | 이미지 처리 장치 및 방법 | |
| WO2019196109A1 (zh) | 一种抑制图像伪彩的方法及装置 | |
| JP2004343685A (ja) | 重み付け勾配ベースの色補正された補間 | |
| JP2010524297A (ja) | パンクロマティック画素を組み込むエッジマッピング | |
| CN110852953B (zh) | 图像插值方法及装置、存储介质、图像信号处理器、终端 | |
| US8836824B2 (en) | Systems and methods for threshold-based luma channel noise reduction | |
| US20070035634A1 (en) | System and method for reduction of chroma aliasing and noise in a color-matrixed sensor | |
| TWI493979B (zh) | 去馬賽克方法、非暫時性機器可讀取儲存媒體以及影像訊號處理器 | |
| Wang et al. | Demosaicing with improved edge direction detection | |
| KR101874538B1 (ko) | 영상의 대비 및 채도 동시 향상시키는 영상 처리 방법 및 장치 | |
| CN107517367B (zh) | 拜尔域图像插值方法、装置、图像处理芯片及存储装置 | |
| KR101803021B1 (ko) | 테일러 급수 및 적응적 가중치 선택에 기반한 디모자이킹 방법 | |
| KR20140006751A (ko) | 이미지 처리 장치 및 방법 | |
| Susan et al. | Edge strength based fuzzification of colour demosaicking algorithms | |
| KR20190036253A (ko) | 그라디언트 기반 rgbw cfa 디모자킹 장치 및 방법 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 18914684 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 18914684 Country of ref document: EP Kind code of ref document: A1 |